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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Global biomass supply modeling for long-run management of the climate system

Bioenergy is projected to have a prominent, valuable, and maybe essential, role in climate management. However, there is significant variation in projected bioenergy deployment results, as well as concerns about the potential environmental and social implications of supplying biomass. Bioenergy deployment projections are market equilibrium solutions from integrated modeling, yet little is known about the underlying modeling of the supply of biomass as a feedstock for energy use in these modeling frameworks. We undertake a novel diagnostic analysis with ten global models to elucidate, compare, and assess how biomass is supplied within the models used to inform long-run climate management. With experiments that isolate and reveal biomass supply modeling behavior and characteristics (costs, emissions, land use, market effects), we learn about biomass supply tendencies and differences. The insights provide a new level of modeling transparency and understanding of estimated global biomass supplies that informs evaluation of the potential for bioenergy in managing the climate and interpretation of integrated modeling. For each model, we characterize the potential distributions of global biomass supply across regions and feedstock types for increasing levels of quantity supplied, as well as some of the potential societal externalities of supplying biomass. We also evaluate the biomass supply implications of managing these externalities. Finally, we interpret biomass market results from integrated modeling in terms of our new understanding of biomass supply. Overall, we find little consensus between models on where biomass could be cost-effectively produced and the implications. We also reveal model specific biomass supply narratives, with results providing new insights into integrated modeling bioenergy outcomes and differences. The analysis finds that many integrated models are considering and managing emissions and land use externalities of supplying biomass and estimating that environmental and societal trade-offs in the form of land emissions, land conversion, and higher agricultural prices are cost-effective, and to some degree a reality of using biomass, to address climate change.

09 BIOMASS FUELS↗
DOE OSTI2024

Schrödinger Cats and Quantum Complementarity

Complementarity tells us we cannot know precisely the values of all the properties of a quantum object at the same time: the precise determination of one property implies that the value of some other (complementary) property is undefined. E.g. the precise knowledge of the position of a particle implies that its momentum is undefined. Here we show that a Schrödinger cat has a well defined value of a property that is complementary to its “being dead or alive” property. Then, thanks to complementarity, it has an undefined value of the property “being dead or alive”. In other words, the cat paradox is explained through quantum complementarity: of its many complementary properties, any quantum system, such as a cat, can have a well defined value only of one at a time. Schrödinger’s cat has a definite value of a property which is complementary to “being dead or alive”, so it is neither dead nor alive. Figuratively one can say it is both dead and alive. While this interpretation only uses textbook concepts (the Copenhagen interpretation), apparently it has never explicitly appeared in the literature. We detail how to build an Arduino based simulation of Schrödinger’s experiment based on these concepts for science outreach events.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Optimal decision trees for categorical data via integer programming

Decision trees have been a very popular class of predictive models for decades due to their interpretability and good performance on categorical features. However, they are not always robust and tend to overfit the data. Additionally, if allowed to grow large, they lose interpretability. In this paper, we present a mixed integer programming formulation to construct optimal decision trees of a prespecified size. We take the special structure of categorical features into account and allow combinatorial decisions (based on subsets of values of features) at each node. Our approach can also handle numerical features via thresholding. Here we show that very good accuracy can be achieved with small trees using moderately-sized training sets. The optimization problems we solve are tractable with modern solvers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Weak Ferroelectricity and Leakage Current Behavior of Multiferroic CoCr{sub 2}O{sub 4} Nanomaterials

Multiferroic CoCr{sub 2}O{sub 4} is synthesized by low-temperature sol-gel auto combustion technique. High energy synchrotron x-ray diffraction pattern confirms the single-phase cubic structure with space group Fd3m. Average crystallite size (17.91 nm) and negative micro-strain (9.86 × 10{sup −4}) are estimated by Williamson–Hall (W-H) plot. FTIR confirms the formation of spinel metal oxide-based cobalt chromites. The strong decrease in ε′ and tan δ at higher frequency can be interpreted by Maxwell-Wagner-type interfacial polarization. Weak ferroelectricity is mainly attributed to the partial reversal of polarization. J-E characteristic reveals the Ohmic (I–V) and Child’s square law (I–V{sup 2}) behavior observed in CoCr{sub 2}O{sub 4} nanomaterials with slope value ~ 1.04 and ~ 1.6, respectively. The conduction process for the leakage current density is interpreted using the space-charge limited current (SCLC) mechanism.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

A Numerical Investigation of the Pinning Phenomenon in Quasi-Periodic Frenkel Kontrova Model Under an External Force

We perform a numerical study on Frenkel–Kontrova (FK) models in quasi-periodic media subject to a constant external force. The quasi-periodic FK models appear in several physical problems such as deposition, spin waves in 1-D, planar dislocations in 3-D either in a quasi-crystal or on a cleaved surface with irrational slopes of a periodic crystal. The phenomenon that we study is pinning. When there is no force, the very homogeneous equilibria are abundant, but when there is a constant force, the uniformly distributed equilibrium states just slide away and the physically relevant equilibria are configurations with frequencies (inverse of densities in some interpretation) that are resonant with the frequencies of the medium. We use a dynamical interpretation of the equilibrium equation and perform a systematic Monte-Carlo exploration of the equilibria. We study the geometry and quantitative properties of the equilibria after the application of a constant external force. This leads to several quantitative regularities on the abundance and geometric properties of the pinned states in the models we consider. This complements recent qualitative studies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Radiochronometric discordance in cast uranium metal: a multi-laboratory intercomparison exercise

Here, the model age of a nuclear material is crucial in nuclear forensic analysis. Uranium metals with complex production histories often exhibit discordant model ages from the 230 Th– 234 U and 231 Pa– 235 U chronometers. Recent studies involving targeted uranium metal castings have enhanced our understanding of decay product behavior during casting, aiding nuclear forensic interpretation. Building on this prior work, forensics laboratories at Atomic Weapons Establishment (AWE), Lawrence Livermore National Laboratory (LLNL), and Los Alamos National Laboratory (LANL) conducted an interlaboratory comparison to investigate spatial heterogeneity in uranium metal cast under controlled conditions. Each laboratory measured samples of a mixed feedstock and its corresponding cast product. This work furthers our understanding of discordant model ages and the use of discordance as a signature to enhance confidence in interpretations of radiochronometric data for nuclear forensics.

230Th/234U↗
DOE OSTI2018

Cluster Method of Constructing Bethe Approximation for the Ising Model of a Dilute Magnet

The paper offers an interpretation of Bethe approximation based on comparison of spin clusters of different sizes on the Cayley tree. Based on this interpretation, the authors suggested the method to construct Bethe approximation for the node- or bond-diluted Ising magnet. The method provides an accurate value of the percolation threshold for the Bethe lattice. For different variations of this method, the authors constructed spontaneous magnetizations at zero and final temperatures as a function of concentration of magnetic atoms and found an analytical expression for the critical indicator of the correlation length.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Inverse regression for ridge recovery: a data-driven approach for parameter reduction in computer experiments

Parameter reduction can enable otherwise infeasible design and uncertainty studies with modern computational science models that contain several input parameters. In statistical regression, techniques for sufficient dimension reduction (SDR) use data to reduce the predictor dimension of a regression problem. A computational scientist hoping to use SDR for parameter reduction encounters a problem: a computer prediction is best represented by a deterministic function of the inputs, so data comprised of computer simulation queries fail to satisfy the SDR assumptions. To address this problem, here we interpret SDR methods sliced inverse regression (SIR) and sliced average variance estimation (SAVE) as estimating the directions of a ridge function, which is a composition of a low-dimensional linear transformation with a nonlinear function. Within this interpretation, SIR and SAVE estimate matrices of integrals whose column spaces are contained in the ridge directions’ span; we analyze and numerically verify convergence of these column spaces as the number of computer model queries increases. Moreover, we show example functions that are not ridge functions but whose inverse conditional moment matrices are low-rank. Consequently, the computational scientist should beware when using SIR and SAVE for parameter reduction, since SIR and SAVE may mistakenly suggest that truly important directions are unimportant.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Coupling Ambient Pressure X-ray Photoelectron Spectroscopy with Density Functional Theory to Study Complex Surface Chemistry and Catalysis

Ambient pressure X-ray photoelectron spectroscopy (APXPS) experiments narrow the pressure and materials gaps between UHV surface science experiments and applications. Upon closing these gaps, ambiguity can enter the analysis of the spectra due to overlapping peaks from different elements or functional groups of both the sample and the gas phase. Additionally, reaction intermediates and mechanisms are often inaccessible from interpretation of APXPS data alone. In many cases, these issues can be overcome with the aid of density functional theory (DFT) calculations. Here, we outline our process of combining DFT calculations with APXPS experiments by describing our recent investigations of the adsorption of dimethyl methylphosphonate (DMMP) on MoO3 and CuO. We begin by showing the importance of the characterization of the isolated gas phase molecule before adsorption onto a surface. In particular, strong agreement between theory and experiment helps identify plausible decomposition pathways of the isolated molecule and provides a baseline for interpretation of spectra showing evidence of DMMP interaction with surfaces. The intact adsorption of DMMP on MoO3 offers an illustration of how moving beyond pristine single crystalline surfaces in calculations can enable better modeling of experimental trends that result from surface defects. Studies of DMMP adsorption on CuO exemplify the powerful synergy of APXPS combined with DFT for elucidation of complex reaction mechanisms on surfaces.

Chemistry↗
DOE OSTI2016

Hierarchical Model for the Analysis of Scattering Data of Complex Materials

Interpreting the results of scattering data for complex materials with a hierarchical structure in which at least one phase is amorphous presents a significant challenge. Often the interpretation relies on the use of large-scale molecular dynamics (MD) simulations, in which a structure is hypothesized and from which a radial distribution function (RDF) can be extracted and directly compared against an experimental RDF. This computationally intensive approach presents a bottleneck in the efficient characterization of the atomic structure of new materials. Here, we propose and demonstrate an approach for a hierarchical decomposition of the RDF in which MD simulations are replaced by a combination of tractable models and theory at the atomic scale and the mesoscale, which when combined yield the RDF. We apply the procedure to a carbon composite, in which graphitic nanocrystallites are distributed in an amorphous domain. We compare the model with the RDF from both MD simulation and neutron scattering data. Ultimately, this procedure is applicable for understanding the fundamental processing-structure-property relationships in complex magnetic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Adversarial Ensemble Modeling of Multi-modal Mechanical Properties for Iron-Based Alloys

Mechanical properties of alloys are controlled by their microstructure; and microstructure evolution is controlled by internal and external stressors. Chemical complexity during the alloy processing may result in heterogeneity and observation of multimodal performance patterns. Thus, to ensure the desired performance of stressed components it is important to understand the origin and mechanisms of such behavior. Adversarial ensemble modeling was introduced here to explain multimodal mechanical properties of the iron-based alloys. The modeling results showed that the areas of a single mechanism predominance were contiguous across the alloy compositions clustered by similarity, with sharp and persistent boundaries separating the single-mechanism domains. The marginal compositions resulted in increased competition between the adversarial models but only led to the multimodal behavior when the competing models diverged. Transparency of the clustering method allowed explicit interpretation of the chemistries leading to such competition. The adversarial ensemble was interpreted through transition from ductile to brittle microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Prediction of Creep-Induced Strain Using a Symbolic Regression-Based Model

Material creep under high-temperature conditions limits the lifetime and safety of structural systems such as advanced nuclear reactors. Conventional creep testing is slow and often produces inconsistent results across nominally identical experiments, making lifetime prediction uncertain. Here, to address these challenges, this work develops a data-driven symbolic regression (SR) model that consolidates results from duplicate creep tests and predicts the remaining strain-time curve of an ongoing experiment. The method uses piece-wise multi-objective SR with physical constraints to generate analytic, interpretable functions describing transient creep strain. Applied to Inconel Alloy 617 data, the approach achieved relative mean absolute errors of 1.0–9.5%, providing closed-form predictions of strain evolution. These results demonstrate a first step toward reducing the duration and cost of long-term creep testing while retaining physically interpretable model forms.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Eco-driving Profile Optimization by Dynamic Programming for Battery Electric Vehicles

Although full automation has not yet been achieved, automated vehicles are a valid research area. Not only would automated vehicles provide ultimate driver convenience, but they would maximize energy efficiency by eliminating undesired human driving behaviors and optimally controlling the powertrain. From the perspective of control related to energy saving, speed profile optimization is important for improving system efficiency and satisfying passenger demands. This study employs Dynamic Programming (DP) to solve the constrained optimal problem for travel time, distance, and speed limit by exploring all possible control options. The solutions obtained by DP demonstrate consistent control patterns combining four control modes-acceleration, cruising, coasting, and braking, with cruising or coasting being selective depending on the boundary conditions. Further, this study introduces DP-based simulation results and attempts to provide comprehensive interpretations of the optimal policy by analyzing the essential factors that affect the control problem, including boundary conditions, road load, and powertrain characteristics. Based on these interpretations, the control concepts can be explained as the optimal policy selecting the best control option based on system efficiency and boundary conditions. The results of DP are compared with a human-like driver model to show that the optimal speed profiles can effectively reduce energy consumption.

Autonomous vehicles↗
DOE OSTI2019

Clinical performance of Rb-82 myocardial perfusion PET and Tc-99m-based SPECT in patients with extreme obesity

Background: We evaluated the performance of stress imaging with technetium-99m-labeled tetrofosmin single-photon emission computed tomography (SPECT) and rubidium-82 positron emission tomography (PET) in patients with extreme obesity, defined as body mass index ≥40 kg/m{sup 2}. Methods: We identified patients with extreme obesity who underwent angiography in our center and either stress SPECT or PET within the previous six months. Cohorts of patients with extreme obesity and a <5% pretest likelihood of CAD who underwent SPECT (N = 25) or PET (N = 25) were also included. Results: In total, 108 patients who underwent SPECT (N = 57) or PET (N = 51) were identified. Scan interpretation was classified as definitely normal or abnormal in 83.3% of PET and 60.5% of SPECT scans, respectively (P < .01). PET demonstrated higher diagnostic accuracy and normalcy rate. PET was found to have higher specificity for the pooled cohort. Similar findings were observed using stenosis cut-offs of ≥50% and ≥70%. Conclusions: In patients with extreme obesity, PET enabled more definitive scan interpretation with less artifact compared to SPECT. PET provided higher diagnostic accuracy and specificity in the detection of obstructive coronary artery disease.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Diagnostic assessment of reservoir response to fracturing: a case study from Hydraulic Fracturing Test Site (HFTS) in Midland Basin

Abstract This paper outlines a data collection and diagnostics case study involving multiple horizontal shale wells. We look at well production profiles using rate transient analysis, differences in near wellbore complexity, geologic variations within the area of interest, as well as compositional differences in the rocks based on cores obtained from within the stimulated reservoir. The Hydraulic Fracturing Test Site is a multi-well experiment involving stimulation of unconventional shale wells in the southeastern Midland portion of the Permian Basin. The targeted formations include both the upper as well as the middle Wolfcamp formations, also referred alternatively as Wolfcamp A and Wolfcamp B. Data integration and analysis shared in this paper help us understand the various geologic controls impacting well productivity, particularly the wide variance observed between the Wolfcamp A and Wolfcamp B formations. Rate transient analysis indicates similar system permeabilities for stimulated wells. However, we observe higher effective fracture half-lengths for upper Wolfcamp wells. Using observations from 3D seismic interpretations (such as pad scale faults) as well as petrophysical and image log data, we highlight the substantial differences in stimulation as we move along the well laterals from the heel toward the toe sections. These differences are further reconciled with observations from zones with high data density at the core locations through stimulated rock, as well as independent data such as microseismic emissions. At the test site, Wolfcamp A was found to be relatively quartz rich with significant heterogeneity whereas Wolfcamp B is richer in clay and organic content. This impacts the geomechanical characteristics of the rock mass with much higher natural fracture density in the shallower interval. Thus, the fracture growth is more uniform in the deeper interval and more heterogeneous with branching likely in upper interval. Increased complexity also leads to consistently better productivity from the wells in the shallower interval as demonstrated from RTA results. This case study is unique because it provides valuable insights from actual sampling of the stimulated zones in hydraulically fractured wells and helps understand impact of various factors that contribute toward variability in well production. The findings from this study provides insights into need for optimization of completion designs in the various Wolfcamp landing zones, such as optimization of cluster or fracture spacing in various Wolfcamp intervals. In addition, it provides a useful template for data collection and research direction in future field test sites of similar nature in unconventional reservoirs.

Energy & Fuels↗
DOE OSTI2018

Improvement in the Mass Resolution of Single Particle Mass Spectrometry Using Delayed Ion Extraction

A specific delayed ion extraction (DIE) technique, which combines a standard rectangular extraction pulse with an exponential pulse, was introduced for a single particle mass spectrometry (SPMS) instrument, and it can focus ions in a wide mass range and results in a mass resolution improvement for the mass range of the studied ions. The experimental results indicate that the average mass resolution for positive ions is about 1000 when the mass-to-charge ratio (m/z) is greater than 70, and for negative ions, when the m/z is greater than 70, the average resolution can reach 2000. The highest mass resolutions achieved so far are 1260 for positive ions and 2400 for negative ions for SPMS, which are very beneficial for mass peak interpretation and chemical compound identification. The primary applications for atmospheric particle measurements show that the high mass resolution of SPMS with the DIE technique is very beneficial for the analysis of carbon and metallic element containing particles, and {sup 39}K{sup +} with C{sub 3}H{sub 3}{sup +} and {sup 41}K{sup +} and C{sub 3}H{sub 5}{sup +} in organic particles were successfully differentiated using SPMS. The results indicate that SPMS with DIE technique can significantly ease mass peak interpretation and improve the mass assignment ability during analysis. Furthermore, existing SPMS instruments can be improved by a facile retrofitting process to implement the DIE technique. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Highlights from the Pierre Auger Observatory

The Pierre Auger Observatory is the world’s largest cosmic ray observatory. Our current exposure reaches nearly 40,000 km 2 sr and provides us with an unprecedented quality data set. In this highlight, the performance and stability of the detectors and their enhancements are described. Data analyses have led to a number of major breakthroughs. Among these, we discuss the energy spectrum and the searches for large-scale anisotropies. We present analyses of our X max data and show how it can be interpreted in terms of mass composition. We also describe some new analyses that extract mass-sensitive parameters from the 100 % duty cycle surface detector (SD) data. A coherent interpretation of all these recent results opens new directions. The consequences regarding the cosmic ray composition and the properties of ultrahigh-energy cosmic ray (UHECR) sources are briefly discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Data Mining and Visualization of High-Dimensional ICME Data for Additive Manufacturing

Integrated computational materials engineering (ICME) methods combining CALPHAD with process-based simulations can produce rich, high-dimensional data for alloy and process design. In ICME methods for metallurgical applications, the visualization and interpretation of such high-dimensional data has previously been through heat maps represented in 2 or 3 dimensions. While such an approach is ideal when one variable is varied at a time, in the case of high-dimensional data with multiple variables varied simultaneously, as is the case in additive manufacturing, interpreting the trends through two- or three-dimensional heat maps becomes challenging. Here, we propose a strategy of mixed visual data mining and quantitative analysis for high-dimensional metallurgical and process data using high-throughput thermodynamic calculations. Two case studies show the application of the proposed approach. The first case study investigated the effects of feedstock chemistry on the δ ferrite formation in 316L stainless steel powders used for binder jet additive manufacturing. The second case study linked Scheil–Gulliver calculations to a process model for dissimilar joining of aluminum alloys 5356 and 6111 during laser hot-wire additive manufacturing. Both cases contained thousands of calculated data points, showcasing the utility of visual data analysis through parallel coordinate plotting, Pearson correlation coefficient matrices, and scatter matrices compared to traditional process maps. These visualization techniques can be extended to many additive manufacturing problems to capture process–structure–property relationships for additively manufactured components.

36 MATERIALS SCIENCE↗